TDWI Articles

Data Digest: Addressing Concerns about AI and ML

Systemic ML problems, reservations about AI applications in healthcare, and advice for businesses governing AI.

 

Research into ML Failure

A study by Stanford's Center for Research on Foundation Models reveals systemic failures in machine learning ecosystems that can lead to problems for applications such as hiring, medical imaging, and speech recognition.

Read more at Stanford University


Problems for Healthcare and AI

Issues including data bias, privacy problems, and a lack of transparency mean that integrating AI into healthcare poses risks to patient care and safety.

Read more at Information Week


Regulating and Governing AI

Businesses need to address the legal and data governance implications of generative AI today.

Read more at SC Media


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